Detecting Protein Variants within Mass Spectrometry Datasets

An important aim of cancer proteomics is to understand how the cancer proteome, with all its variation in both protein sequence and protein abundance, emerges from aberrations characterized within cancer genomic and transcriptomic datasets. A challenge in reaching this goal is that standard mass-spectrometry-based onco-proteomic strategies typically ignore variations in protein sequences, instead characterizing cancer proteomes in terms of changing abundances of standard reference proteins. In this thesis, I assess strategies for incorporating information about protein sequence variation within standard proteomics analysis strategies. I develop a pipeline for the characterization of variations within protein sequences and assess the best methodology to do so.Ph.D